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Utilização de técnicas bayesianas em modelos de regressão de Poisson para dados de contagem longitudinais e dados de contagem com medidas repetidas apresentando excesso de zeros
(Universidade Federal de São Carlos, 2008-06-09) Tsuchiya, Nilton; Achcar, Jorge Alberto; https://lattes.cnpq.br/3125027713681936; https://lattes.cnpq.br/9389137037683221
In medical and biological researches we often .nd count data. For longitudinal count data, usual Poisson regression models, assuming independence among observations, are not applicable because of the correlation of these measures. This work presents hierarchical Bayesian models considering random e¤ects to analyze longitudinal count data. A Normal and a Gamma distribution are considered to these e¤ects besides the mixture of Normal distributions. We also present zero in.ated Poisson (ZIP) regression models for repeated measures. Markov Chain Monte Carlo (MCMC) is used to estimate the parameters. Keywords: Longitudinal Count Data; Poisson Regression Model; Zero In.ated Model; Hierarchical Model; Bayesian Analysis; MCMC Methods.
Estimação de escores binomiais correlacionados: uma aplicação em Credit Scoring
(Universidade Federal de São Carlos, 2008-06-09) Souza, Victor Hugo Delvalle; Louzada Neto, Francisco; https://lattes.cnpq.br/0994050156415890; https://lattes.cnpq.br/8756605556928181
For the most part of modelings in the credit risk area, the most widely used model is the credit scoring, and as the main statistical technique, the binary logistic regression, used to determine whether a customer is a good or bad payer. In this academic work an alternative methodology is proposed, where the estimative is formed based on the scores obtained by customers; this means the response follows a binomial distribution. In this modeling the combined estimate of scores of various products used by customers is included, considering the correlation between these scores.